a national COVID-19 surveillance platform using anonymised individual patient-level records from all 940 general practices in Scotland, deterministically linked to multiple datasets recording morbidity, mortality, virology, vaccination, and prescribing (appendix p 1). Linkage was done with a unique identifier for each resident in Scotland who is registered with a GP.
Immunisation contraindicated was recorded for nearly one fifth of all unvaccinated individuals for whom a reason was documented. Laboratory records identified 254 049 individuals with no vaccination record who were tested at least once for SARS-CoV-2 by RT-PCR since the start of the pandemic. Non-hospital-based prescription records identified 416 499 individuals with no vaccination record who had been prescribed medication of any description since Jan 1, 2019. 285 647 unvaccinated individuals had interacted with the unscheduled care pathway (one or more of NHS 24, out-of-hours GP consultations, or the Scottish Ambulance Service), while 133 569 people with no vaccination record had at least one hospital admission according to the Scottish Morbidity Records. In total, 268 740 individuals with no evidence of vaccination were identified in any of the above data sources.
573 289 eligible individuals aged 18 years or older were identified as having no record of any COVID-19 vaccination in Scotland and at least one contact with NHS Scotland since Jan 1, 2019. We then excluded people who had died since the start of the vaccination programme, and those for whom immunisation contraindicated was recorded as the reason for non-vaccination. On Aug 10, 2022, our method identified 494 288 individuals with no record of any COVID-19 vaccination.
On the basis of GP records, the majority (298 866, 60·5%) of 494 288 unvaccinated individuals were not known to have any comorbidities, compared with 1 988 751 (51·7%) of 3 847 789 vaccinated individuals, whereas 55 122 (11·2%) of 494 288 unvaccinated individuals were recorded as having three or more comorbidities, compared with 481 019 (12·5%) of 3 847 789 vaccinated individuals. The most frequently reported comorbidities among 494 288 unvaccinated individuals were chronic respiratory disease (77 643, 15·7%), depression (63 375, 12·8%), and hypertension (52 474, 10·6%).
One in five (103 505, 20·9%) of 494 288 unvaccinated individuals were prescribed medications for conditions relating to the CNS, compared with 655 531 (17·0%) of 3 847 789 vaccinated individuals, with more than a third of this unvaccinated group (40 179 [38·8%] of 103 505) prescribed antidepressants.
Multivariable logistic regression modelling was used to identify the factors most likely to predict COVID-19 vaccination. Male sex, high deprivation, living in large urban areas, being prescribed medication for CNS disorders, and having more than three comorbidities were most associated with unvaccinated status, although individuals with some comorbidities—such as hypertension, diabetes, and chronic respiratory disease—were more likely to be vaccinated.
Notably, although increasing age and presence of comorbidities are among the most widely recognised risk factors for COVID-19 mortality,
people with a substantial number of comorbidities remained at increased risk of being unvaccinated.
Additionally, although our approach minimises false inflation of the number of unvaccinated people, some of these individuals will have had no recent interaction with the health-care system and so will remain undetected. Unvaccinated people might also be less likely to have health-seeking behaviour, reducing the chance of them being detected through this method.
Some individuals might have been vaccinated outside of Scotland, which was not captured in our analysis. Identifying people vaccinated in other countries will improve future estimates of unvaccinated populations.
In summary, this national analysis revealed that, even after accounting for possible overinflation of population size, a considerable proportion of the adult population of Scotland remains unvaccinated against COVID-19. We also identified predictors of unvaccinated status, which can help with formulating a revised national vaccination strategy.
AS and CR are members of the Scottish Government Chief Medical Officer’s COVID-19 Advisory Group. AS is a member of the NERVTAG Risk Stratification Subgroup and an unfunded member of AstraZeneca’s COVID-19 strategic consultancy group, the Thrombocytopenia Taskforce. CR is a member of the Scientific Pandemic Influenza Group on Modelling and the Medicines and Healthcare Products Regulatory Agency COVID-19 Vaccine Benefit and Risk Working Group. JLKM is a member of the COVID Scottish National Incident Management Team. CM reports research funding from the Medical Research Council, Health Data Research UK, National Institute for Health Research, and the Scottish Chief Science Office. All other authors declare no competing interests. EAVE II is funded by the Medical Research Council with the support of BREATHE, the health data research hub for respiratory health, which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. Additional support was provided through Public Health Scotland and the Scottish Government Director-General Health and Social Care. The research for this Correspondence is part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation. UA and CM acknowledge funding from Health Data Research UK (Measuring and Understanding Multimorbidity using Routine Data in the UK—HDR-9006; CFC0110). The funding source had no involvement in data collection, study design, data analysis, interpretation of findings, or the decision to publish this Correspondence. We thank Dave Kelly (Albasoft, Inverness, UK) for support with making primary care data available, Iain Mclaughlin (Public Health Scotland, Glasgow, UK) for help with the identification of the unvaccinated cohort, and James Pickett (Health Data Research UK, London, UK), Wendy Inglis-Humphrey, Vicky Hammersley, Maria Georgiou, Laura Gonzalez Rienda (Usher Institute, University of Edinburgh, Edinburgh, UK), Morna Coote, Amanda Burridge, Amie Wilson, and Megan Gorman (Public Health Scotland, Glasgow, UK) for project management and administration support. We acknowledge the support of the EAVE II Patient Advisory Group for their help with interpretation of findings and suggestions for dissemination and engagement. SSH and EH contributed equally. AS and CR contributed equally.
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Published: 24 September 2022
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